The present invention is in the field of data analysis and relates to detection of abnormalities in a data stream. The invention is particularly useful in video analysis systems where there is a need to detect abnormal behavior of objects (e.g. people or vehicles) in a region of interest.
Analysis of data in different fields includes various tasks and techniques. Many applications aim at identifying data pieces, e.g. indicating certain events or objects in a region of interest, and enabling the system (or a user) to decide whether a certain data piece is to be classified as normal or abnormal with respect to a standard behavior under the observed conditions. For example, most video analytics systems analyze existence of objects in the video frame utilizing certain rules which typically require a priori knowledge of types of events which are abnormal in the scene. Such data analysis systems may require different types of set of rules, but are generally incapable of automatically generating the set of rules based on observed behavior of the sample data to be analyzed.